World: r3wp

or have a look at cassandra and/or monetdb (w/o knowing anything 
about your intended usage)

yeah, I've looked a a few

rdf is to xml what War and Peace is to Cat in the Hat -- Triples 
are working even with Maxim's code above (just not in hashes for 
more than a query with a single value).. but i crave the speed of 
index? against large datasets.

I WILL NOT STOP TILL I HAVE A FAST AND SIMPLE TRIPLE STORE!  
(sleep is my enemy)

terry, index? is not a procedure within rebol .. its the same as 
length?
its a stored value which is simply looked up when you call index?


nothing will be as fast as index?    its the "getting to" index which 
consumes cycles

Where's the dilema ? you just have to maintain 3 indexes at the same 
time (for triples), there isn't any other choice if you looking for 
speed on readings.

i know .. keys can be integers that are indexes of values in map! 
or hash.

yeah Steeve, im scratching out notes on that now.. it's not quite 
as simple as it sounds

ie: a value might be a large binary ..

1 GB values as keys don't work very well.

I already said to you to compute a checksum to build keys from large 
data, it's built-in in Rebol

yeah, but then you risk collisions

with an md5 checksum ??? don't be silly :-)

you can negate collisions by building two checksums out of different 
properties of you data and merging them.

fair enough.. not running bank accounts with this thing

the other issue is the time it takes to build the checksum vs brute 
force

but it will be 100 or 1000 times faster, then to access the data 
using an index.

your actual trial to make a lookup with foreach or find+loop is insanly 
slow by comparison

Got to decide what is more important:
-- time to build data structure
-- time to update it (add/remove on the fly)
-- time to search it

And build data structures optimized to your priorities. There is 
no one true solution, just the best match for the situation at hand.

*current trial

ok.. here's an example.. 

take this simple rdf triple   "Tweety" "isa" "Canary"
How would create 3 indexes to manage it and 10,000,000 like it?

It's the problem, I think Terry can't decide :-)

Ok, I give it to you...

Tweety
 "age" "75"
Steeve
 "isa" "Rebol"
Steeve
 "age" "unknown"

I have a system working now that's fast enough.. but I'm a speed 
junkie.. there must be a BEST way (not better... BEST)

First i add the triple in the triples store (a simple block)

The, I recovers its index from the block (actually it's the last 
one)

And i use this index as the value for the 3 indexes, and i create 
the keys+value
Tweety
: index
Isa
: index
Canary
: index

that's all...

yeah, but ...

Perhaps the explanations are not clear, but it's pretty clear in 
my head ;-)

>> ie: ["Tweety" "isa" "canary"]
== ["Tweety" "isa" "canary"]
>> index? find ie "Tweety"
== 1

Great.. now what

( only in Rebol does ie: actually mean ie: )

(added In index1) "Tweety"= index
(added In index2) "Isa"= index
(added In index3) "Canary"= index

(added In index1) "Tweety"= index
(added In index2) "Isa"= index
(added In index3) "Canary"= index

so now i want to query, say , everything that is "age" "75" (like 
above)

by doing, index2/"age" you'll get all the triple having the verb 
"age"

with index3/"75", you'll get those with 75 as the target

then intersect the 2 blocks

I just think you don't get it, but I know my explanation sucks, sorry.

i get it.

Ron Everett presented  a database that did much of what you want 
at DevCon2007. The live discussion is here:

   http://www.rebol.org/aga-display-posts.r?offset=0&post=r3wp500x1919
The video of the presentation may be on qtask.

yeah, associative stuff :-)

Senteces from Lazysoft was another product of such kind ...

i remember that

http://www.rebol.net/cgi-bin/r3blog.r?view=0161

And my comment...

it's remember me the IDE Plex(obsydian) in the nineties. it used 
widely the concept of triples (tuples) to modelize applications and 
databases.

hmm, i thought i got it. :( now I'm lost in block hell

nope.. i got it again :)

Should have listened to my mother and became a lawyer.